Showing papers in "Journal of Intelligent and Robotic Systems in 2012"
TL;DR: The paper shows how an UAS can automatically obtain information in real-time of the evolution of the fire front shape and potentially other parameters related to the fire propagation by means of on-board infrared or visual cameras.
Abstract: The paper presents an Unmanned Aircraft System (UAS), consisting of several aerial vehicles and a central station, for forest fire monitoring. Fire monitoring is defined as the computation in real-time of the evolution of the fire front shape and potentially other parameters related to the fire propagation, and is very important for forest fire fighting. The paper shows how an UAS can automatically obtain this information by means of on-board infrared or visual cameras. Moreover, it is shown how multiple aerial vehicles can collaborate in this application, allowing to cover bigger areas or to obtain complementary views of a fire. The paper presents results obtained in experiments considering actual controlled forest fires in quasi-operational conditions, involving a fleet of three vehicles, two autonomous helicopters and one blimp.
364 citations
TL;DR: In this paper, a Matlab-based path planning tool was developed, collecting four separate approaches: geometric predefined trajectories, manual waypoint definition, automatic waypoint distribution, and a comprehensive A*-based algorithm used to generate paths, minimizing risk of collision with orographic obstacles.
Abstract: The graph-search algorithms developed between 60s and 80s were widely used in many fields, from robotics to video games. The A* algorithm shall be mentioned between some of the most important solutions explicitly oriented to motion-robotics, improving the logic of graph search with heuristic principles inside the loop. Nevertheless, one of the most important drawbacks of the A* algorithm resides in the heading constraints connected with the grid characteristics. Different solutions were developed in the last years to cope with this problem, based on post-processing algorithms or on improvements of the graph-search algorithm itself. A very important one is Theta* that refines the graph search allowing to obtain paths with "any" heading. In the last two years, the Flight Mechanics Research Group of Politecnico di Torino studied and implemented different path planning algorithms. A Matlab based planning tool was developed, collecting four separate approaches: geometric predefined trajectories, manual waypoint definition, automatic waypoint distribution (i.e. optimizing camera payload capabilities) and a comprehensive A*-based algorithm used to generate paths, minimizing risk of collision with orographic obstacles. The tool named PCube exploits Digital Elevation Maps (DEMs) to assess the risk maps and it can be used to generate waypoint sequences for UAVs autopilots. In order to improve the A*-based algorithm, the solution is extended to tri-dimensional environments implementing a more effective graph search (based on Theta*). In this paper the application of basic Theta* to tri-dimensional path planning will be presented. Particularly, the algorithm is applied to orographic obstacles and in urban environments, to evaluate the solution for different kinds of obstacles. Finally, a comparison with the A* algorithm will be introduced as a metric of the algorithm performances.
170 citations
TL;DR: A survey of motion planning techniques under uncertainty with a focus on their application to autonomous guidance of unmanned aerial vehicles (UAVs), providing a roadmap for tackling the UAV guidance problem.
Abstract: This paper provides a survey of motion planning techniques under uncertainty with a focus on their application to autonomous guidance of unmanned aerial vehicles (UAVs). The paper first describes the primary sources of uncertainty arising in UAV guidance and then describes relevant practical techniques that have been reported in the literature. The paper makes a point of distinguishing between contributions from the field of robotics and artificial intelligence, and the field of dynamical systems and controls. Mutual and individual contributions for these fields are highlighted providing a roadmap for tackling the UAV guidance problem.
149 citations
TL;DR: A model to evaluate the coverage of a given UAS and a ground station capable of swapping a UAV’s batteries are proposed, followed by a discussion of prototype components and tests of some of the prototype modules.
Abstract: Future Unmanned Aircraft Systems (UASs) are expected to be nearly autonomous and composed of heterogeneous Unmanned Aerial Vehicles (UAVs). While most of the current research focuses on UAV avionics and control algorithms, ground task automation has come to the attention of researchers during the past few years. Ground task automation not only relieves human operators, but may also expand the UAS operation area, improve system coverage and enable operation in risky environments without posing a threat to humans. We propose a model to evaluate the coverage of a given UAS. We also compare different solutions for various modules of an automated battery replacement system for UAVs. In addition, we propose a ground station capable of swapping a UAV's batteries, followed by a discussion of prototype components and tests of some of the prototype modules. The proposed platform is well-suited for high-coverage requirements and is capable of handling a heterogeneous UAV fleet.
143 citations
TL;DR: The design of a system to emulate a flying, dexterous mobile manipulator for mobile manipulation by an unmanned aerial vehicle with dexterous arms and end effectors is described.
Abstract: Given significant mobility advantages, UAVs have access to many locations that would be impossible for an unmanned ground vehicle to reach, but UAV research has historically focused on avoiding interactions with the environment. Recent advances in UAV size to payload and manipulator weight to payload ratios suggest the possibility of integration in the near future, opening the door to UAVs that can interact with their environment by manipulating objects. Therefore, we seek to investigate and develop the tools that will be necessary to perform manipulation tasks when this becomes a reality. We present our progress and results toward a design and physical system to emulate mobile manipulation by an unmanned aerial vehicle with dexterous arms and end effectors. To emulate the UAV, we utilize a six degree-of-freedom miniature gantry crane that provides the complete range of motion of a rotorcraft as well as ground truth information without the risk associated with free flight. Two four degree-of-freedom manipulators attached to the gantry system perform grasping tasks. Computer vision techniques and force feedback servoing provide target object and manipulator position feedback to the control hardware. To test and simulate our system, we leverage the OpenRAVE virtual environment and ROS software architecture. Because rotorcraft are inherently unstable, introduce ground effects, and experience changing flight dynamics under external loads, we seek to address the difficult task of maintaining a stable UAV platform while interacting with objects using multiple, dexterous arms. As a first step toward that goal, this paper describes the design of a system to emulate a flying, dexterous mobile manipulator.
118 citations
TL;DR: This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles by using Mixed Integer Linear Programming (MILP) to find paths that meet mission objectives, are safe with respect to collision and grounding, fuel efficient and satisfy criteria for communication.
Abstract: We will in this paper address the problem of offline path planning for Unmanned Aerial Vehicles (UAVs). Our goal is to find paths that meet mission objectives, are safe with respect to collision and grounding, fuel efficient and satisfy criteria for communication. Due to the many nonconvex constraints of the problem, Mixed Integer Linear Programming (MILP) will be used in finding the path. Approximate communication constraints and terrain avoidance constraints are used in the MILP formulation. To achieve more accurate prediction of the ability to communicate, the path is then analyzed in the radio propagation toolbox SPLAT!, and if the UAVs are not able to communicate according to design criteria for bandwidth, constraints are modified in the optimization problem in an iterative manner. The approach is exemplified with the following setup: The path of two UAVs are planned so they can serve as relay nodes between a target without line of sight to the base station.
112 citations
TL;DR: This paper proposes a novel underwater robot, employing a spherical hull and equipped with multiple vectored water-jet-based thrusters, and demonstrates that the motion characteristics of this type of underwater robot are acceptable, and the design is worthy of further research.
Abstract: Research on underwater robots is attracting increased attention around the world. Various kinds of underwater robots have been developed, using an assortment of shapes, sizes, weights, and propulsion methods. In this paper, we propose a novel underwater robot, employing a spherical hull and equipped with multiple vectored water-jet-based thrusters. The overall design of the robot is first introduced, and the mechanical structure and electrical system are then individually described. Two important mechanical components are the spherical hull and the waterproof box, and these are discussed in detail. Detailed descriptions of the two-level architecture of the electrical system and the design of the water-jet thrusters are also given. The multiple vectored water-jet-based propulsion system is the key feature of the robot, and the experimental mechanism of this system is briefly explained. The three main principles behind the propulsion system are also presented. Finally, evaluation experiments are presented to verify the basic motions of a prototype robot. The experimental results demonstrate that the motion characteristics of this type of underwater robot are acceptable, and the design is worthy of further research.
106 citations
TL;DR: In this work a comprehensive review of UAV vision based attitude estimation approaches is covered, starting from horizon based methods and passing by vanishing points, optical flow, and stereoscopic based techniques.
Abstract: Unmanned aerial vehicles (UAVs) are increasingly replacing manned systems in situations that are dangerous, remote, or difficult for manned aircraft to access. Its control tasks are empowered by computer vision technology. Visual sensors are robustly used for stabilization as primary or at least secondary sensors. Hence, UAV stabilization by attitude estimation from visual sensors is a very active research area. Vision based techniques are proving their effectiveness and robustness in handling this problem. In this work a comprehensive review of UAV vision based attitude estimation approaches is covered, starting from horizon based methods and passing by vanishing points, optical flow, and stereoscopic based techniques. A novel segmentation approach for UAV attitude estimation based on polarization is proposed. Our future insightes for attitude estimation from uncalibrated catadioptric sensors are also discussed.
88 citations
TL;DR: In this article, a quad-rotor robotic platform equipped with a visual and inertial motion estimation system was developed for autonomous take-off, positioning, navigation and landing in unknown environments.
Abstract: This paper presents the development of a quad-rotor robotic platform equipped with a visual and inertial motion estimation system. Our objective consists of developing a UAV capable of autonomously perform take-off, positioning, navigation and landing in unknown environments. In order to provide accurate estimates of the UAV position and velocity, stereo visual odometry and inertial measurements are fused using a Kalman Filter. Real-time experiments consisting on motion detection and autonomous positioning demonstrate the performance of the robotic platform.
86 citations
TL;DR: An intelligent automated disassembly cell for online (real time) selective disassembly is proposed that is composed of an industrial robotic manipulator, a camera, range sensing and component segmentation visual algorithms.
Abstract: In this study, we propose an intelligent automated disassembly cell for online (real time) selective disassembly. The cell is composed of an industrial robotic manipulator, a camera, range sensing and component segmentation visual algorithms. The cell prototype allows for robotic sensory-driven disassembly under uncertainty. An online genetic algorithm model for selective disassembly is also proposed for optimal and near/optimal disassembly sequencing.
82 citations
TL;DR: The architecture, algorithms and real-world benchmarks performed by Johnny Jackanapes, an autonomous service robot for domestic environments are described and novel and robust algorithms centered around multi-modal human robot interaction, semantic scene understanding and SLAM are described.
Abstract: In this article we describe the architecture, algorithms and real-world benchmarks performed by Johnny Jackanapes, an autonomous service robot for domestic environments. Johnny serves as a research and development platform to explore, develop and integrate capabilities required for real-world domestic service applications. We present a control architecture which allows to cope with various and changing domestic service robot tasks. A software architecture supporting the rapid integration of functionality into a complete system is as well presented. Further, we describe novel and robust algorithms centered around multi-modal human robot interaction, semantic scene understanding and SLAM. Evaluation of the complete system has been performed during the last years in the RoboCup@Home competition where Johnnys outstanding performance led to successful participation. The results and lessons learned of these benchmarks are explained in more detail.
TL;DR: An automated UAV based data acquisition and outdoor site reconstruction system using a coarse digital surface model (DSM) with minimal data preprocessing and a developed view planning heuristic that considers a coverage, a maximum view angle and an overlapping constraint imposed by multi-view stereo reconstruction techniques.
Abstract: Multi-view stereo algorithms are an attractive technique for the digital reconstruction of outdoor sites. Concerning the data acquisition process a vertical take off and landing UAV carrying a digital camera is a suitable platform in terms of mobility and flexibility in viewpoint placement. We introduce an automated UAV based data acquisition and outdoor site reconstruction system. A special focus is set on the problem of model based view planning using a coarse digital surface model (DSM) with minimal data preprocessing. The developed view planning heuristic considers a coverage, a maximum view angle and an overlapping constraint imposed by multi-view stereo reconstruction techniques. The time complexity of the algorithm is linear with respect to the size of the area of interest. We demonstrate the efficiency of the entire system in two scenarios, a building and a hillside.
TL;DR: This paper describes the modeling, control and hardware implementation of an experimental tilt-rotor aircraft that combines the high-speed cruise capabilities of a conventional airplane with the hovering capability of a helicopter by tilting their four rotors.
Abstract: This paper describes the modeling, control and hardware implementation of an experimental tilt-rotor aircraft. This vehicle combines the high-speed cruise capabilities of a conventional airplane with the hovering capabilities of a helicopter by tilting their four rotors. Changing between cruise and hover flight modes in mid-air is referred to transition. Dynamic model of the vehicle is derived both for vertical and horizontal flight modes using Newtonian approach. Two nonlinear control strategies are presented and evaluated at simulation level to control, the vertical and horizontal flight dynamics of the vehicle in the longitudinal plane. An experimental prototype named Quad-plane was developed to perform the vertical flight. A low-cost DSP-based Embedded Flight Control System (EFCS) was designed and built to achieve autonomous attitude-stabilized flight.
TL;DR: The synthesis and the onboard implementation of the control law are described and the flight testing of the fixed-wing UAV in hover, transition, and cruise modes are described.
Abstract: There is renewed interest in tail-sitter airplanes on account of their vertical takeoff and landing capability as well as their efficient horizontal flight capabilities. The transition from a vertical near-hover mode to a horizontal cruise mode is a critical component of the tail-sitter flight profile. In practice, this transition is often achieved by a stall-and-tumble maneuver, which is somewhat risky and therefore not desirable, so alternative maneuvering strategies along controlled trajectories are sought. Accordingly, this paper presents the synthesis and application of a transition controller to a tail-sitter UAV for the first time. For practical reasons, linear controllers are designed using the PID technique and linked by gain scheduling. The limits of the PID controller are complemented by a so-called $\mathcal{L}_{1}$ adaptive controller that considers the coupling effect, reduces the effort for appropriate gain selection, and improves the tracking performance at different points during operation. Each transition trajectory is controlled by the flight velocity and path angle using dynamic inversion. The transition control law is tested on a tail-sitter UAV, an 18-kg vehicle that has a 2-m wingspan with an aspect ratio of 4.71 and is powered by a 100-cm3 gasoline engine driving an aft-mounted ducted fan. This paper describes not only the synthesis and the onboard implementation of the control law but also the flight testing of the fixed-wing UAV in hover, transition, and cruise modes.
TL;DR: This paper focuses on the topic of smooth gait transition of a hexapod robot by a proposed central pattern generator (CPG) algorithm, which is constructed by an isochronous oscillators and several first-order low-pass filters.
Abstract: This paper focuses on the topic of smooth gait transition of a hexapod robot by a proposed central pattern generator (CPG) algorithm. Through analyzing the movement characteristics of the real insects, it is easy to generate kinds of gait patterns and achieve their smooth transition if we employ a series of oscillations with adjustable phase lag. Based on this concept, a CPG model is proposed, which is constructed by an isochronous oscillators and several first-order low-pass filters. As an application, a hexapod robot and its locomotion control are introduced by converting the CPG signal to robot’s joint space. Simulation and real world experiment are completed to demonstrate the validity of the proposed CPG model. Through measuring the position of the body center and the distance between footpoints and ground, the smooth gait transition can be achieved so that the effectiveness of the proposed method is verified.
TL;DR: It is shown that, under the proposed adaptive NN control, the tracking error of each manipulator converges to an adjustable neighborhood of the origin under the Lyapunov analysis.
Abstract: In this paper, we investigate the mutual synchronization control problem of multiple robot manipulators in the case that the desired trajectory is only available to a portion of the team members, and the dynamics and the external disturbances of the manipulators are unknown. Treating the weighted average of the outputs of the neighbors as the reference trajectory, an adaptive neural network (NN) tracking control is designed for each manipulator. Based on the Lyapunov analysis, rigid mathematical proof is provided for the proposed algorithm for both state feedback and output feedback cases. It is shown that, under the proposed adaptive NN control, the tracking error of each manipulator converges to an adjustable neighborhood of the origin. Simulations are provided to demonstrate the effectiveness of the proposed approach.
TL;DR: A robust system for enabling robots to detect and identify humans in domestic environments is proposed through the use of thermal and visual information sources that are integrated to detect human-candidate objects and face detection, and face recognition to identify them.
Abstract: In this paper a robust system for enabling robots to detect and identify humans in domestic environments is proposed. Robust human detection is achieved through the use of thermal and visual information sources that are integrated to detect human-candidate objects, which are further processed in order to verify the presence of humans and their identity using face information in the thermal and visual spectrums. Face detection is used to verify the presence of humans, and face recognition to identify them. Active vision mechanisms are employed in order to improve the relative pose of a candidate object/person in case direct identification is not possible. The response of the different modules is characterized, and the proposed system is validated using image databases of real domestic environments, and human detection and identification benchmarks of the [email protected] research community.
TL;DR: This model is shown to satisfy the necessary conditions to the existence of a non-linear observer (Thau) when proper assumptions for the actuation forces are made, and can thus be used to generate diagnostic residuals inside a Fault Detection (FD) system.
Abstract: This paper addresses the problem of sensor fault detection for a wide class of Unmanned Vehicles (UVs). First a general model for UVs, based on the dynamics of a 6 Degrees Of Freedom (6-DOF) rigid body, subject to gravity and actuation forces, is presented. This model is shown to satisfy the necessary conditions to the existence of a non-linear observer (Thau) when proper assumptions for the actuation forces are made. The observer can thus be used to generate diagnostic residuals inside a Fault Detection (FD) system. Finally, the proposed approach is customized for sensor fault detection on an unmanned quad-rotor vehicle, and simulation results show the effectiveness of the adopted solution.
TL;DR: An extended model that includes the availability of humans in the environment is presented, and it is demonstrated how a navigation planner can incorporate this information to plan paths that increase the likelihood that a robot can find an available helper when it needs one.
Abstract: Robots are increasingly autonomous in our environments, but they still must overcome limited sensing, reasoning, and actuating capabilities while completing services for humans. While some work has focused on robots that proactively request help from humans to reduce their limitations, the work often assumes that humans are supervising the robot and always available to help. In this work, we instead investigate the feasibility of asking for help from humans in the environment who benefit from its services. Unlike other human helpers that constantly monitor a robot's progress, humans in the environment are not supervisors and a robot must proactively navigate to them to receive help. We contribute a study that shows that several of our environment occupants are willing to help our robot, but, as expected, they have constraints that limit their availability due to their own work schedules. Interestingly, the study further shows that an available human is not always in close proximity to the robot. We present an extended model that includes the availability of humans in the environment, and demonstrate how a navigation planner can incorporate this information to plan paths that increase the likelihood that a robot can find an available helper when it needs one. Finally, we discuss further opportunities for the robot to adapt and learn from the occupants over time.
TL;DR: An ego-localization method that combines measurements of a GPS receiver, odometers, a gyrometer, a video camera and a virtual 3D city model is described and an obstacle detection method based on the comparison between the image acquired by the on-board camera and the image extracted from the 3D model is proposed.
Abstract: In this paper, we propose to study the integration of a new source of a priori information, which is the virtual 3D city model. We study this integration for two tasks: vehicles geo-localization and obstacles detection. A virtual 3D city model is a realistic representation of the evolution environment of a vehicle. It is a database of geographical and textured 3D data. We describe an ego-localization method that combines measurements of a GPS (Global Positioning System) receiver, odometers, a gyrometer, a video camera and a virtual 3D city model. GPS is often consider as the main sensor for localization of vehicles. But, in urban areas, GPS is not precise or even can be unavailable. So, GPS data are fused with odometers and gyrometer measurements using an Unscented Kalman Filter (UKF). However, during long GPS unavailability, localization with only odometers and gyrometer drift. Thus, we propose a new observation of the location of the vehicle. This observation is based on the matching between the current image acquired by an on-board camera and the virtual 3D city model of the environment. We also propose an obstacle detection method based on the comparison between the image acquired by the on-board camera and the image extracted from the 3D model. The following principle is used: the image acquired by the on-board camera contains the possible dynamic obstacles whereas they are absent from the 3D model. The two proposed concepts are tested on real data.
TL;DR: A novel dynamic approach to relay-chain concept is proposed to maintain the communication between vehicles, and simulation results show that an airborne communication relay can be established autonomously by using artificial potential filed based autonomous path planning approach.
Abstract: As a result of unmanned aerial vehicles being widely used in different areas, studies about increasing the autonomous capabilities of unmanned aerial vehicles are gaining momentum. Today, unmanned aerial vehicle platforms are especially used in reconnaissance, surveillance and communications areas. In this study, in order to achieve continuous long-range communication relay infrastructure, artificial potential field based path planning of Unmanned Aerial Vehicles is discussed. A novel dynamic approach to relay-chain concept is proposed to maintain the communication between vehicles. Besides dynamically keeping vehicles in range and appropriate position to maintain communication relay, artificial potential field based path planning also provides collision avoidance system. The performance of the proposed system is measured by applying a simulation under the Matlab Simulink and Network Simulator environment. Artificial potential field based flight patterns are generated in Matlab, and performance of the communication between vehicles is measured in Network Simulation environment. Finally the simulation results show that an airborne communication relay can be established autonomously by using artificial potential filed based autonomous path planning approach. Continues state communication is provided by obtaining a resistant communication relay which depends on artificial potential field based positioning algorithm.
TL;DR: This paper presents an implementation of computer vision to hold a quadrocopter aircraft in a stable hovering position using a low-cost, consumer-grade, video system and proposes a slight modification of the Kalman filter to account for this delay.
Abstract: The requirement that mobile robots become independent of external sensors, such as GPS, and are able to navigate in an environment by themselves, means that designers have few alternative techniques available. An increasingly popular approach is to use computer vision as a source of information about the surroundings. This paper presents an implementation of computer vision to hold a quadrocopter aircraft in a stable hovering position using a low-cost, consumer-grade, video system. However, such a system is not able to stabilize the aircraft on its own and must rely on a data-fusion algorithm that uses additional measurements from on-board inertial sensors. Special techniques had to be implemented to compensate for the increased delay in the closed-loop system with the computer vision system, i.e., video timestamping to determine the exact delay of the vision system and a slight modification of the Kalman filter to account for this delay. At the end, the validation results of the proposed filtering technique are presented along with the results of an autonomous flight as a proof of the proposed concept.
TL;DR: A comprehensive design of a Gun Launched Micro Air Vehicle (GLMAV) is presented and a detailed GLMAV nonlinear mathematical model is presented for hover and near-hover flight conditions and identified from experimental load data using a strain-gage aerodynamic balance.
Abstract: A comprehensive design of a Gun Launched Micro Air Vehicle (GLMAV) is presented. The GLMAV rotorcraft is a new Micro Air Vehicle (MAV) concept using two-bladed coaxial contra-rotating rotors and a cyclic swashplate. The MAV packaged in a projectile is launched using the energy delivered by a portable weapon. When it reaches the apogee, the projectile is transformed in such a way that the MAV becomes operational over the zone to be observed. A detailed GLMAV nonlinear mathematical model is presented for hover and near-hover flight conditions and identified from experimental load data using a strain-gage aerodynamic balance. Simplifications brought to the aerodynamic submodel have permitted its linearization in the parameter space. The parameter estimation was based on the Kalman filter estimation method applied to the simplified aerodynamic model and using the input-output data from the experiment. The persistently exciting condition is given in terms of physical variables of the GLMAV through two simple expressions. The identification results are presented and validated through comparisons between the model output and real load data.
TL;DR: The proposed strategy is a time-invariant feedback control design with the distinguishing feature that it requires almost no switching compared to alternative methodologies of the same nature.
Abstract: This paper suggests a new way for nonholonomic mobile robots to navigate in obstacle environments using potential fields based on navigation functions. The proposed strategy is a time-invariant feedback control design with the distinguishing feature that it requires almost no switching compared to alternative methodologies of the same nature. Asymptotic convergence with collision avoidance for the proposed approach is established analytically, and the method is demonstrated on a differential-drive skid steering mobile robot.
TL;DR: A quadrotor test bench that can test and verify the 6 DOF flight controller is presented and the results indicate the feasibility and the value of the test bench.
Abstract: In this paper, a quadrotor test bench that can test and verify the 6 DOF flight controller is presented. The development of controller for aerial vehicle is usually a long and dangerous procedure. It needs series of tests from simulation to real flight. However, there are differences between simulation and real time flight due to the limit of the current simulation technique. The quadrotor test bench presented in the paper aims to fill the gap between simulation and real time flight. The test bench contains a quadrotor attached on the base through a sphere joint which let the quadrotor be able to rotate around 3 axes. A 6 axes force/torque sensor is used to simulate the position of the aerial vehicle. The paper presents the detailed system design and implementation of the test bench. Furthermore, the modeling and the parameter identification of the quadrotor on the test bench are described. A 6 DOF controller that consists of both guidance controller and attitude controller is designed using a nonlinear control technique named trajectory linearization control (TLC). Finally, the flight tests on the quadrotor test bench are demonstrated. The results indicate the feasibility and the value of the test bench.
TL;DR: The proposed method detects conflicts using an algorithm based on axis-aligned minimum bounding box and solves the detected conflicts cooperatively using a genetic algorithm that modifies the trajectories of the UAVs with an overall minimum cost.
Abstract: This paper presents a Conflict Detection and Resolution (CDR) method for cooperating Unmanned Aerial Vehicles (UAVs) sharing airspace. The proposed method detects conflicts using an algorithm based on axis-aligned minimum bounding box and solves the detected conflicts cooperatively using a genetic algorithm that modifies the trajectories of the UAVs with an overall minimum cost. The method changes the initial flight plan of each UAV by adding intermediate waypoints that define the solution flight plan while maintaining their velocities. The method has been validated with many simulations and experimental results with multiple aerial vehicles platforms based on quadrotors in a common airspace. The experiments have been carried out in the multi-UAV aerial testbed of the Center for Advanced Aerospace Technologies (CATEC).
TL;DR: A modified design of Spherobot, that is better suited to fabrication, is presented and the modified propulsion mechanism and other components of the design are discussed in detail to highlight the challenges of fabrication.
Abstract: In the literature, Spherobot refers to a mobile robot with a spherical exo-skeleton and a propulsion mechanism that uses unbalance masses in a tetrahedral arrangement. A modified design of Spherobot, that is better suited to fabrication, is presented in this paper. The modified propulsion mechanism and other components of the design are discussed in detail to highlight the challenges of fabrication. An adaptive estimation and control algorithm used for position control of the unbalance masses and a steering algorithm used for motion control of Spherobot are also discussed. Experimental results of the Spherobot navigating a hallway with bends is presented.
TL;DR: A set of composite sensor system for tracking the three-dimensional welding seam based on visual sensor and arc sensor technology, which can effectively acquire three- dimensional welding seam information, such as clear images of seam and pool and stable arc voltage signals.
Abstract: Aiming at the shortcomings of teaching-playback robot that can't track the three-dimensional welding seam in real time during GTAW process, this paper designed a set of composite sensor system for tracking the three-dimensional welding seam based on visual sensor and arc sensor technology, which can effectively acquire three-dimensional welding seam information, such as clear images of seam and pool and stable arc voltage signals. The characteristic values of weld image and arc voltage signals were accurately extracted by using proper processing algorithm, and the experiments have been done to verify the precision of processing algorithms. The results demonstrate that the error is very small, which is accurate enough to meet the requirements of the subsequent real-time tracking and controlling during the welding robot GTAW process.
TL;DR: This paper demonstrates how qualitative positional fluents based on a fuzzy set semantics can be deployed in domestic domains and showcases how reasoning with these qualitative notions can seamlessly be applied to a fetch-and-carry task in a RoboCup@Home scenario.
Abstract: In this paper, we present a thorough integration of qualitative representations and reasoning for positional information for domestic service robotics domains into our high-level robot control. In domestic settings for service robots like in the [email protected] competitions, complex tasks such as "get the cup from the kitchen and bring it to the living room" or "find me this and that object in the apartment" have to be accomplished. At these competitions the robots may only be instructed by natural language. As humans use qualitative concepts such as "near" or "far", the robot needs to cope with them, too. For our domestic robot, we use the robot programming and plan language Readylog, our variant of Golog. In previous work we extended the action language Golog, which was developed for the high-level control of agents and robots, with fuzzy set-based qualitative concepts. We now extend our framework to positional fuzzy fluents with an associated positional context called frames. With that and our underlying reasoning mechanism we can transform qualitative positional information from one context to another to account for changes in context such as the point of view or the scale. We demonstrate how qualitative positional fluents based on a fuzzy set semantics can be deployed in domestic domains and showcase how reasoning with these qualitative notions can seamlessly be applied to a fetch-and-carry task in a [email protected] scenario.
TL;DR: In this paper, the Harmony Search Algorithm (HSA) is used for automatic detection of circular shapes considering the overall process as an optimization problem, which is based on the derivative free meta-heuristic optimization algorithm inspired by musicians improvising new harmonies while playing.
Abstract: Automatic circle detection in digital images has received considerable attention over the last years in computer vision as several novel efforts aim for an optimal circle detector. This paper presents an algorithm for automatic detection of circular shapes considering the overall process as an optimization problem. The approach is based on the Harmony Search Algorithm (HSA), a derivative free meta-heuristic optimization algorithm inspired by musicians improvising new harmonies while playing. The algorithm uses the encoding of three points as candidate circles (harmonies) over the edge-only image. An objective function evaluates (harmony quality) if such candidate circles are actually present in the edge image. Guided by the values of this objective function, the set of encoded candidate circles are evolved using the HSA so that they can fit into the actual circles on the edge map of the image (optimal harmony). Experimental results from several tests on synthetic and natural images with a varying complexity range have been included to validate the efficiency of the proposed technique regarding accuracy, speed and robustness.